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Apprentice Machine Learning Testing Jobs in New York

Machine Learning at Headspace is a dynamic and innovative group whose mission is to improve the ... Experience with unit, integration, and end-to-end testing, version control * Strong problem solving ...

Machine Learning Engineer

New York, NY · On-site

$150K - $195K/yr

End-to-end machine learning model experience in production; that you've stood up a service including experimenting, training, testing and tuning a job against a dataset all the way through to ...

Staff Machine Learning Engineer

New York, NY · On-site +1

$179K - $224K/yr

About the Staff Machine Learning Engineer at Headspace: The AI & Machine Learning group at ... Experience with unit, integration, and end-to-end testing, version control * Strong problem solving ...

Sr. Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be ... Solve complex problems by writing and testing application code, developing and validating ML models ...

As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and ... Proactively safeguard model and system quality through testing, monitoring, validation, and ...

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Apprentice Machine Learning Testing information

What kinds of projects or tasks can I expect to work on as an Apprentice Machine Learning Testing?

As an Apprentice Machine Learning Testing, you’ll typically assist in evaluating machine learning models by designing and running tests, analyzing model outputs, and helping identify issues like bias or overfitting. You may work closely with data scientists and software engineers to validate model performance and ensure results align with project objectives. Your daily tasks might include preparing test datasets, executing automated testing scripts, and documenting findings to help improve model reliability. This role often serves as a valuable introduction to practical machine learning workflows and quality assurance processes in technical teams.

What are the key skills and qualifications needed to thrive as an Apprentice Machine Learning Testing, and why are they important?

To thrive as an Apprentice in Machine Learning Testing, a foundational understanding of statistics, programming (especially Python), and basic machine learning concepts is essential, often supported by a degree or coursework in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, Jupyter Notebooks, and version control systems is typically required. Strong analytical thinking, attention to detail, and effective communication skills help apprentices collaborate and identify testing issues efficiently. These skills ensure accurate model validation, effective troubleshooting, and contribute to the robust deployment of machine learning solutions.

What does an Apprentice Machine Learning Testing do?

An Apprentice Machine Learning Testing professional assists in evaluating and validating machine learning models to ensure they perform as expected. They typically work under the guidance of experienced data scientists or engineers, running tests, analyzing results, and helping to identify issues such as bias or inaccuracies in algorithms. Their responsibilities may also include developing test cases, writing reports, and learning about data preprocessing and evaluation metrics. This role is ideal for those who are new to the field and want to build foundational skills in machine learning quality assurance.

What is the difference between Apprentice Machine Learning Testing vs Machine Learning Engineer?

AspectApprentice Machine Learning TestingMachine Learning Engineer
Required CredentialsBasic understanding of ML concepts, often pursuing relevant certifications or degreesAdvanced degrees (BSc, MSc, PhD) in CS or related fields, with extensive experience
Work EnvironmentEntry-level, supervised testing environments, often in training programsFull-time, independent development and deployment of ML models in production
Employer & Industry UsageInternships, training programs, entry-level roles in tech companiesEstablished tech firms, startups, research institutions

Apprentice Machine Learning Testing roles focus on learning and assisting with testing ML models under supervision, while Machine Learning Engineers design, build, and deploy ML systems independently. The apprentice position is ideal for gaining foundational skills, whereas the engineer role requires advanced expertise and experience.

What are popular job titles related to Apprentice Machine Learning Testing jobs in New York? For Apprentice Machine Learning Testing jobs in New York, the most frequently searched job titles are:
What job categories do people searching Apprentice Machine Learning Testing jobs in New York look for? The top searched job categories for Apprentice Machine Learning Testing jobs in New York are:
What cities in New York are hiring for Apprentice Machine Learning Testing jobs? Cities in New York with the most Apprentice Machine Learning Testing job openings:
Principal Machine Learning Engineer

Principal Machine Learning Engineer

Headspace

New York, NY • On-site, Remote

$207K - $258K/yr

Full-time

Medical, Retirement

Re-posted 6 days ago


Job description

About the Principal Machine Learning Engineer at Headspace:
Machine Learning at Headspace is a dynamic and innovative group whose mission is to improve the experiences of our members and clinicians through the mindful application of Machine Learning. These applications include building conversational AI systems, healthcare assistance tools, and recommendation and personalization systems. In this team, you'll be tasked with owning and delivering cutting edge language-based ML applications that will power the core features of Headspace. You'll have the opportunity to lead the vision, alignment, development, deployment, and adoption of these solutions, helping to bring Headspace to the forefront of AI and to realize its mission to improve health and happiness of the world.
What you will do:
  • Technical Leadership: Lead the development of complex, scalable AI models and applications from inception to production. Drive impactful ML technology initiatives that will shape the delivery of and access to mental healthcare. Serve as a go-to expert and mentor, exemplifying excellence in AI/ML engineering and inspiring others to pursue technical career growth.
  • Shape ML Platform Architecture: Drive the design, development, and evolution of our internal ML platform, taking it from high-level vision to robust implementation.
  • Collaborative Problem-Solving: Partner with cross-functional teams to align technical decisions with organizational goals, ensuring cohesive and impactful solutions.

What you will bring:
Required Skills:
  • Master's of Science degree or higher in Computer Science, Statistics, Mathematics or a related field OR equivalent experience
  • 8+ years of ML engineering experience in an academic or professional setting, programming in Python
  • 8+ years of experience with any of the following fundamental technologies: vector search, embedding models, recommender systems, supervised, unsupervised machine learning, deep learning, reinforcement learning, LLM orchestration, RAG systems.
  • 5+ years of experience with modern NLP tools and machine learning libraries (scikit-learn, PyTorch, TensorFlow, spaCy)
  • Experience with unit, integration, and end-to-end testing, version control
  • Strong problem solving and communication skills and ability to influence across internal organizations
  • Mentorship of junior engineers and contribution to DEIB initiatives

Preferred Skills:
  • PhD in relevant field or equivalent experience
  • Professional experience with clinical and/or healthcare applications of machine learning
  • Familiarity with current ML literature including optimization methods and agent-based models
  • Experience with implementation of robust and highly scalable services
  • Experience with AWS, including SageMaker, Lambda, S3, DynamoDB, IAM

Location: This role is open to candidates across the US, with preferred locations in San Francisco, CA (hybrid), New York City, NY (remote), and Seattle, WA (remote). Candidates must permanently reside in the US full-time.
If your primary residence is in the greater San Francisco Bay Area, this role follows our hybrid model, with 3 days per week in office to support in-person collaboration. Your recruiter will share more details.
Pay & Benefits:
The anticipated new hire base salary range for this full-time position is $162,000-$225,000 + equity + benefits.
For candidates based in San Francisco, New York City, or Seattle, a separate salary range of $207,000-$258,700 applies, consistent with our location-based compensation philosophy.
Our salary ranges are based on the job, level, and location, and reflect the lowest to highest geographic markets where we are hiring for this role within the United States. Within this range, individual compensation is determined by a candidate's location as well as a range of factors including but not limited to: unique relevant experience, job-related skills, and education or training.
Your recruiter will provide more details on the specific salary range for your location during the hiring process.
At Headspace, base salary is but one component of our Total Rewards package. We're proud of our robust package inclusive of: base salary, stock awards, comprehensive healthcare coverage, monthly wellness stipend, retirement savings match, lifetime Headspace membership, generous parental leave, and more. Additional details about our Total Rewards package will be provided during the recruitment process.
About Headspace
Headspace exists to provide every person access to lifelong mental health support. We combine evidence-based content, clinical care, and innovative technology to help millions of members around the world get support that's effective, personalized, and truly accessible whenever and wherever they need it.
At Headspace, our values aren't just what we believe, they're how we work, grow, and make an impact together. We live them daily: Make the Mission Matter, Iterate to Great, Own the Outcome, and Connect with Courage. These values shape our decisions, guide our collaborations, and define our culture. They're our shared commitment to building a more connected, human-centered team-one that's redefining how mental health care supports people today and for generations to come.
Why You'll Love Working Here:
A mission that matters-with impact you can see and feel
A culture that's collaborative, inclusive, and grounded in our values
The chance to shape what mental health care looks like next
Competitive pay and benefits that support your whole self
How we feel about Diversity, Equity, Inclusion and Belonging:
Headspace is committed to bringing together humans from different backgrounds and perspectives, providing employees with a safe and welcoming work environment free of discrimination and harassment. We strive to create a diverse & inclusive environment where everyone can thrive, feel a sense of belonging, and do impactful work together.
As an equal opportunity employer, we prohibit any unlawful discrimination against a job applicant on the basis of their race, color, religion, gender, gender identity, gender expression, sexual orientation, national origin, family or parental status, disability*, age, veteran status, or any other status protected by the laws or regulations in the locations where we operate. We respect the laws enforced by the EEOC and are dedicated to going above and beyond in fostering diversity across our workplace.
*Applicants with disabilities may be entitled to reasonable accommodation under the terms of the Americans with Disabilities Act and certain state or local laws. A reasonable accommodation is a change in the way things are normally done which will ensure an equal employment opportunity without imposing undue hardship on Headspace. Please inform our Talent team by filling out this form if you need any assistance completing any forms or to otherwise participate in the application or interview process.
Headspace participates in the E-Verify Program.
Privacy Statement
All member records are protected according to our Privacy Policy. Further, while employees of Headspace (formerly Ginger) cannot access Headspace products/services, they will be offered benefits according to the company's benefit plan. To ensure we are adhering to best practice and ethical guidelines in the field of mental health, we take care to avoid dual relationships. A dual relationship occurs when a mental health care provider has a second, significantly different relationship with their client in addition to the traditional client-therapist relationship-including, for example, a managerial relationship.
As such, Headspace requests that individuals who have received coaching or clinical services at Headspace wait until their care with Headspace is complete before applying for a position. If someone with a Headspace account is hired for a position, please note their account will be deactivated and they will not be able to use Headspace services for the duration of their employment.
Further, if Headspace cannot find a role that fails to resolve an ethical issue associated with a dual relationship, Headspace may need to take steps to ensure ethical obligations are being adhered to, including a delayed start date or a potential leave of absence. Such steps would be taken to protect both the former member, as well as any relevant individuals from their care team, from impairment, risk of exploitation, or harm.
For how how we will use the personal information you provide as part of the application process, please see: https://www.headspace.com/applicant-notice